Combine the data and the tree using comparative.data() to ready the tree for pgls. Note: if you used dplyr in the steps above, you need to change the class of the resulting dataframe, because there is a bug in caper and it won’t deal with a dplyrtbl_df object. You can use this line of code to fix it class(dataframeFromDplyr) <- "data.frame"

Plot the trimmed tree that includes just the taxa of interest in the astragalus dataset. Make it as beautiful as you can.

Perform PGLS to test the hypothesis that log(B) is a function of log(DistRad), while controlling for phylogenetic signal. Be sure to include the geometric mean of these measurements (square root of their product) as a covariate to control for body size. Is this hypothesis supported?

Plot log(B) as a function of log(DistRad), and color code the points by habitat type.